Termite detection system

ABSTRACT

A method and apparatus of detecting termites in which microwaves are transmitted into a region and reflected microwaves are detected. The received signals are processed to identify the presence or otherwise of termites or other insects. Various hardware configurations and signal processing algorithms are described including planar antenna arrays and neural net signal processing. The system comprises a microwave assembly, modulator and a processor. Microwaves are transmitted into a structure and the reflected microwaves are received in the microwave assembly. The output of the processor is displayed on a display.

FIELD OF THE INVENTION

THIS INVENTION relates to pest detection by transmitting a microwavesignal into a part of a building or other structure for example a wall,floor or ceiling and processing reflections or modulations of themicrowave signal to provide a signal indicative of the presence of apest.

BACKGROUND TO THE INVENTION

Timber eating termites cause damage to property such as buildings. Thereare numerous ways of killing such pests, however, it is not always easyto detect their presence. As a result, a building structure can beseverely damaged by these pests before they are detected. The inventionis directed to detecting pests such as termites or other insects,preferably before they cause appreciable damage.

The problem of detecting termites has been addressed in the past butwithout success. Reference may be had to U. S. Pat. No. 5,285,668 in thename of Robbins and Mueller that describes a system for detectingwood-destroying insects by sensing acoustic emissions generated by theinsects as they feed. The major shortcoming of this approach is thattermites are not always feeding. The inventors have found that termitesmay use extensive galleries to move between a feeding region and a nest.The system disclosed in U.S. Pat. No. 5,285,668 will not detect thetermites in the galleries. Furthermore, acoustic techniques are prone tospurious signals due to ambient noise.

It is known to use microwaves to kill termites and other insects. Thiscan be hazardous due to the relatively large amounts of high frequencypower required to be transmitted in order to kill such insects.Furthermore, the microwaves are generally only used once the insects aredetected which may be after the insects have inflicted large andnoticeable amounts of damage to the building.

OBJECT OF THE INVENTION

It is an object of the present invention to provide a method and systemfor detecting pests, such as termites, by the use of microwaves.

Further objects will be evident from the following description.

DISCLOSURE OF THE INVENTION

In one form, although it need not be the only or indeed the broadestform, the invention resides in a method of detecting insects in astructure including the steps of:

transmitting a near field microwave signal into a part of the structure;

receiving a receive signal dependent on the near field signal; and

processing the receive signal to provide an output signal indicative ofthe presence of the insects in the near field microwave signal.

In preference the step of transmitting a near field microwave signalinvolves transmitting a modulated signal. The modulation may be inamplitude, frequency or phase and is suitably in the audio range.

Preferably, the step of transmitting is further characterised by thenear field microwave signal being less than 2 meters from a transmittertransmitting said signal. More preferably, the signal is less than 1meter from the transmitter. Most preferably the transmitter is closelyadjacent or abutting said part of the building, thereby the near fieldmicrowave signal is less than ½ meter from the transmitter. The step oftransmitting may be further characterised by the near field signal beingnormal to said part of the structure.

Suitably, the near field microwave signal is circular polarized.

The receive signal is preferably a reflected signal.

Preferably, the method is further characterised by the steps oftransmitting and receiving being effected by a common antenna. Suitablythe antenna may be monostatic or bistatic. The antenna may be a horn,apertured printed circuit board, dish, or any other suitable antenna.

Suitably, in one aspect, the step of receiving includes the step ofmixing the signal dependent on the near field signal with a referencesignal to provide a receive signal which is a combined signal.

Suitably the combined signal comprises a beat frequency signalcomponent.

The step of receiving a receive signal may involve receiving a signalsynchronous with the modulation frequency of the transmitted signal.

Preferably, the step of processing may also include the steps offiltering and amplifying the receive signal. Filtering and amplifyingmay suitably maximise the beat frequency signal component.

Preferably, the step of filtering is characterised by the filteringbeing effected by a low pass filter having a cut-off frequency of lessthan 50 HZ. More preferably, the cut off frequency is less than 20 HZand most preferably 10 HZ or less.

A band pass filter may suitably be used for the step of filtering inwhich the upper cut-off frequency may be any one of the above describedvalues and the lower cut-off frequency being approximately 0.01 HZ.

In a further aspect of the invention the step of processing furtherincludes the steps of digitizing and analysing the receive signal toprovide said output signal or output data indicative of the presence ofsaid insects in said near field microwave signal.

In a yet further form, the step of analysing may include analysis ofspectral characteristics of the receive signal.

Suitably, said analysis of spectral characteristics includes Fouriertransformation.

The step of processing the receive signal alternatively includesadaptive recognition of termite indicative signals. The adaptiverecognition may suitably be performed in a neural network. A hiddenMarkov chain processor and/or a Kalman filter may suitably be employedat the input to the neural network to enhance the signal to noise ratioof the signal input to the neural network.

In a further form, the invention resides in a system for detectinginsects in a structure, the system comprising:

signal generator means operatively coupled to transmitter means tothereby transmit a microwave signal into a part of a structure;

receiver means for receiving signals indicative of the presence orotherwise of insects in a near field of the microwave signal; and

processor means for processing the received signal to provide an outputsignal indicating the presence or otherwise of insects.

The signal generator means is preferably a microwave generator means. AGunn oscillator is a suitable signal generator means.

Preferably, said transmitter means is adapted to transmit a circularpolarized field. The transmitter means preferably comprises atransmitting antenna which may be a horn, apertured printed circuitboard, dish, or other suitable antenna.

The receiver means preferably comprises a receiving antenna which maysuitably be the same as the transmitting antenna.

In preference the system further comprises modulator means operativelycoupled to the signal generator means for modulating the transmittedmicrowave signal at a selected frequency.

The receiver means may suitably comprise a synchronous rectifier forlocking on receive signals synchronous with the modulated transmittedmicrowave signal.

The receiver means further comprise mixing means operatively coupled tothe receiving antenna and the signal generator means, said mixing meansproviding a receive signal dependent upon an indicative signal receivedfrom said receiving antenna and a reference signal from said signalgenerator. The receive signal is a combined signal.

In one form, the processor means includes filter means for filteringsaid combined signal, wherein said combined signal comprises a beatfrequency component.

The filter means is suitably adapted to reject frequencies other thanfrequencies indicative of the presence of insects in the near field,such insects typically being termites.

Preferably, the filter means is a low pass filter having a cut-offfrequency of less than 50 HZ. More preferably, less than 20 HZ and mostpreferably 10 HZ or less.

The filter means may be a band pass filter in which the upper cut-offfrequency may be any one of the above frequencies and the lower cut-offfrequency may be approximately 0.01 HZ.

The processor means may include amplification means for amplifying thecombined signal which may be filtered by said filter means.

The processor means may suitably include digitizing means operativelycoupled to a microprocessor for providing said output signal.

In one aspect the processor means is a microprocessor performing one ormore of digitizing, amplifying and filtering tasks in software.

The microprocessor may be programmed with a neural network algorithmand/or a hidden Markov chain processor algorithm and, optionally, aKalman filter. The microprocessor may also perform such tasks as analogto digital conversion, keypad reading and display control.

In preference, the system further comprises display means for displayingthe output signal. The display means may be an audio output, a needlemeter or a visual display unit.

BRIEF DETAILS OF THE DRAWINGS

To assist in understanding the invention preferred embodiments will nowbe described with reference to the following figures in which:

FIG. 1 is a block diagram of a system for detecting insects;

FIG. 2 is a block diagram of an insect detection system in accordancewith the invention,

FIG. 3 is a circuit diagram of FIG. 2,

FIG. 4 is a circuit diagram of the modulator of FIG. 1; and

FIG. 5 is a circuit diagram of the receiver of FIG. 1.

FIG. 6 depicts an IQ mixer configuration;

FIG. 7 depicts a bistatic radar configuration;

FIGS. 8A-B depicts a planar antenna array;

FIG. 9 is a flow diagram illustrating how the system of FIG. 2 detectsinsects such as termites,

FIG. 10 shows a hardware block diagram for analogue signal processing;

FIGS. 11A-B shows a hardware block diagram and software flowchart forFourier signal processing;

FIGS. 12A-B shows a hardware block diagram and software flowchart foradaptive recognition signal processing;

FIG. 13 is a block diagram of a neural net pattern recognition processorand hidden Markov chain processor with optional Kalman filter;

FIGS. 14A-B are plots of near field microwave radiation patterns;

FIG. 15 is a graph showing the output of FIG. 2 when no insects arepresent in a near field signal;

FIG. 16 shows the output of FIG. 2 indicative of insects in a near fieldsignal, and

FIG. 17 shows a Fourier transform of FIGS. 15 and 16.

In the drawings, like reference numerals refer to like parts.

DETAILED DESCRIPTION OF THE DRAWINGS

Referring to FIG. 1, there is shown a conceptual block diagram of asystem 1 for detecting insects, such as termites. The system 1 comprisesa microwave assembly 2 that transmits a continuous wave microwave signalat a frequency of (for example) 24.125 GHz. The signal may be modulatedby modulator 3.

Signals 4 are transmitted into region 5 to detect the presence orotherwise of termites or other insects. Reflected signals 6 are receivedby the microwave assembly 2. Receive signals 7 are passed to a processor8 that performs the signal processing. Commands and programming may beinput to the processor 8 from the (optional) keypad 9 or from various(optional) diagnostics 10. The output from the processor 8 is displayedon display 11. The display is shown as a visual display unit although inother embodiments it may be, for example, a meter or liquid crystaldisplay. A power supply 12 provides power to elements of the system 1.

Referring to FIG. 2, the elements of the microwave assembly 2 andprocessor 8 are shown in more detail. The microwave assembly includes asignal generator 13 for generating the signal of 24.125 GHZ at a primaryoutput PO of signal generator 13. Primary output PO is connected to areceiver and transmitter unit (or circulator) 14 which is coupled toantenna 15. The receiver/transmitter unit 14 and antenna 15 may beincorporated in a rectangular horn antenna which operates as both atransmitter and receiver. In use, the antenna is located closelyadjacent or in an abutting relationship with the region 5, which is mostoften a wall but may be another part of the structure. Antenna 15 has aface covered with tinted plastics material which acts as a radome.

A secondary output SO of signal generator 13 provides a referencesignal, Ref, to one input of a mixer 16. The other input of mixer 16 isconnected to the receiver circuitry of the receiver/transmitter unit 14,from which a received signal Rs is provided.

Mixer 16 combines reference signal Ref and received signal Rs to providea combined signal Cs comprising a beat frequency component at the outputof mixer 16. The combined signal Cs corresponds to signal 7 of FIG. 1.

FIG. 2 also includes details of processor 8 having an input connected tothe output of mixer 16. Processor 8 includes a band pass filter 17having a lower cut-off frequency of approximately 0.1 HZ and an uppercut-off frequency of 10 HZ.

An output of filter 17 is connected to an amplifier 18, the output ofwhich is connected to an analogue to digital converter 19. Amicroprocessor 20 is coupled to converter 19 to receive and processdigitized data from converter 19 and display an output signal or dataindicative of the presence of insects on a visual display unit 11. Otherinputs may be provided to microprocessor 20 as indicated in FIG. 1. Anadaptive filter may be used to suppress clutter or to render the processspecific to particular insects. The processor 8 may be embodied in apersonal computer with the filter, amplifier and digitizing functionsbeing performed in software or partially in software.

Referring to FIG. 3, there is illustrated a circuit diagram 21corresponding to the microwave assembly 2 and processor 8 of FIG. 2 andtherefore identical components have the same number. Circuit diagram 21includes an oscillator diode D1 for providing the 24.125 GHZ signal toantenna 15 via a circulator 14. Anode of diode D1 is connected to a +5volt power line and diode D1 is in parallel with a series resistorcapacitor filter network R11, C20 which reduces the effects of powerline oscillations.

Circulator 14 isolates the mixer 16 from the oscillator signal by afactor of approximately 200. This provides a leakage signal fromcirculator 14 resulting in a reference signal Ref of 24.125 GHZ to mixer16. Accordingly, reference signal Ref is synchronised to and is the samefrequency as the signal transmitted by antenna 15 which, in the absenceof target motion results in a beat frequency of 0.0 HZ.

Output of mixer 16 is connected to a co-axial cable link L1 couplingmixer 16 to a high pass filter network of capacitor C3 and resistor R5which has a cut-off frequency of 0.1 HZ. Furthermore, there is aresistor R8 which is a DC return resistor for mixer 16. Currents fromsubsequent circuitry are DC blocked by capacitor C3.

The common node of capacitor C3 and resistor R5 are connected to anoperational amplifier 18 the gain of which is dependent upon feedbackresister R1 in which capacitor C1 provides filtering. Further, parallelresistor and capacitor network R2, C11 at the output as operationalamplifier 18 provide a low pass filter having a cut off frequency ofapproximately 10 HZ. Additional filtering and D.C. blocking are providedby resistor capacitor network R6, C2 and R7 in which common node of C2and R7 is connected to a co-axial cable port B2 for connection withdigitizer 19 of FIG. 2.

Operational amplifier 18 has +/−5 volt power rails supplied by standardpower supplies. The +5 volt power rail of diode D1 is supplied from thesame power supply. Resistors R9, R10 and VR2 located between pins oneand eight of operation amplifier 18 are used to select an appropriateoffset voltage.

A detailed schematic circuit diagram of one embodiment of the modulator3 is shown in FIG. 4. An LM555 timer 22 provides a driving frequency ofaround 1 kHz. This frequency is chosen to be well removed from the mainsfrequency of 50 Hz and power line harmonics. It also reduces 1/f noisein the first receiver amplifier. A 4040 flip-flop 23 is used to dividethe fundamental oscillator frequency for a 50% duty cycle. The output 24from the modulator 3 drives the signal generator 13 in the microwaveassembly 2.

The above embodiments have described simple microwave assembliesincorporating mixer detection. Other signal receiving schemes which takeadvantage of the optional modulator may also be employed. A circuitdiagram for one alternate embodiment of a receiver is shown in FIG. 5. Areflected signal is received by microwave diode 25. The microwave diodedetected signal consists of a large bias and a small, superimposedsignal due to the termites. The total signal is first amplified using ahigh pass filter 26 with a cut-in of around 100 Hz. A gain of 10 ischosen to provide an almost square wave output of +/−3 volts withoutsaturating the first amplifier 26.

The signal is amplified in a synchronous amplifier 27 whose gain istoggled between +1 and −1 in phase with the modulation from themodulator 3. The switching is performed by an LTC1043, 28. Any signalthat is synchronous with the modulating frequency results in a DC outputfrom the synchronous amplifier 27. The output from the synchronousamplifier 27 is passed through a narrow band, low offset (chopperstabilized) amplifier 29. A passband of 0.1-10 Hz is selected. Theoutput 30 of the receiver is passed to the processor 8 or may be passeddirectly to the microprocessor 20.

An alternate mixer embodiment is shown in FIG. 6. As with the embodimentof FIG. 3 a microwave signal is generated and transmitted towards atarget 31. The reflected signal 32 is mixed with a reference signal 33from the diode D1. The Q mixer is phased such that the output is leading(or lagging) that of the I mixer by 90°. Motion of the target 31 towardsthe microwave assembly produces circular rotation of a trace on anoscilloscope configured for XY display of the two inputs I and Q. Motionaway from the microwave assembly produces rotation of the oppositesense. Pure amplitude modulation (AM) appears as a straight line ofunity gradient. Amplitude Modulation combined with motion results inerratic trajectories with or without rotation. A skilled operator canrecognise the oscilloscope trace to identify the presence or otherwiseof termites or other insects in the target area.

A bistatic radar configuration is depicted in FIG. 7 for use in theinvention. In this embodiment the transmitting antenna 34 is separatedfrom the receiving antenna 35. A low noise amplifier 36 provides initialamplification of the reflected signal before passing to the mixer 16.The low noise amplifier 36 is suitably a monolithic microwave integratedcircuit (MMIC) with a maximum gain of about 10 dB. Careful positioningof antennas 34 and 35 can minimise the effect of interference due toelements of the structure between the microwave assembly and the targettermites. The intermediate frequency output 7 is passed to the processor8 as described earlier.

A planar antenna array configuration is depicted in FIG. 8. FIG. 8Adepicts a transmitting array 37 comprising sixteen transmittingantennas, such as 38, coupled to microwave source 39, which could be amicrowave diode. The receiver array 40 depicted in FIG. 8B comprisessixteen receiving antennas, such as 41. The planar array configurationhas the advantage that the signals can be combined from a number ofantenna elements to imitate beam steering and focussing. This can bedone with either or both of the transmitter array 37 and receiving array40. Furthermore, redundancy and non-redundancy of signals from differentantenna apertures can be used to enhance desired signals over theclutter. A planar antenna structure is also easy to manoeuvre behindobstacles, such as cupboards, and covers a larger area than a singleelement. In this embodiment the control of the array can be effected bythe microprocessor 20.

Referring to FIG. 9, the method of using the system of FIG. 1 isillustrated in a flowchart. The method is worked with an antenna locatedclosely adjacent to a wall which is suspected to contain termites. Amicrowave field is transmitted at step 41 from a microwave assemblytowards and through the wall. A reflected signal dependent upon nearfield activity (ie. Movement or presence of termites in the wall) isreceived at step 42. This received signal is mixed with a referencesignal to provide a combined signal having a beat frequency which isfiltered at step 43 to select frequencies indicative of the presence oftermites. The filtered signal is then amplified at step 44. Steps 43 and44 may be interchanged depending on the nature and magnitude of thesignal or pre-amplification may be employed prior to filtering. Theresulting signal is then analysed at step 45 and output to some form ofdisplay at step 46. The display may be hard copy, oscilloscope(s), lightemitting diode(s) or audio signal(s).

Steps 43, 44 and 45 constitute the signal processing which can beperformed according to a number of preferred embodiments. Threepreferred embodiments are basic analog signal processing, fixedalgorithm spectral recognition and adaptive recognition.

FIG. 10 depicts a hardware block diagram for basic analog signalprocessing. The output of a microwave mixer 47 is coupled to apre-amplifier 48 and lock-in amplifier 49. The lock-in amplifier 49locks in to signals having a modulation frequency applied by modulator 3(refer FIG. 1). A filter arrangement comprising a high pass filter 50and low pass filter 51 select signals in a frequency range indicative oftermites. Some analog signal processing occurs in display equaliser 52before a final stage amplifier 53 amplifies the signal for display on anoscilloscope, moving coil meter etc.

FIG. 11 depicts a hardware block diagram (FIG. 11A) and softwareflowchart (FIG. 11 B) for a signal processing approach in which a fixedalgorithm is employed to process the signal and compare it with storedtemplates to identify spectral components indicative of termites. Aswith the previous embodiment the signal from the microwave mixer 47 ispassed to pre-amplifier 48 and lock-in amplifier 49. The signal isfiltered in anti-alias filter 54 and digitised in ADC 55. The digitalsignal is passed to microprocessor 56 for signal processing.

The signal processing is depicted in the flowchart of FIG. 11B. Allparameters are initialised 57 and an appropriate initial gain andsoftware controlled digital filter bandpass are set 58. The softwarecontrolled gain and filter bandpass are set to remove as much of theinterference and noise, such as 50 Hz and harmonics, as possible,without affecting the Doppler and AM signal from the insects andvibration. This can be effectively achieved by computing the windowedcovariance of the data time series to determine power spectral density.Ten seconds of data is acquired 59 and a FFT is performed 60. A check ofthe magnitude and frequency of the FFT data is made 61 and if necessarythe gain at 58 is adjusted and new data is acquired. If the data at 61is within parameters it is compared with stored templates 62. Theclosest match is determined 63 and displayed 64. This embodimentprovides a good discrimination between real signals and noise at aminimal hardware an software cost.

A more sophisticated signal processing embodiment is described withreference to FIG. 12 which includes a hardware block diagram in FIG. 12Aand a software flowchart in FIG. 12B. In this embodiment the IQ mixerembodiment of FIG. 6 is employed. The signal from the I channel mixer 65is passed to pre-amplifier 66 and lock-in amplifier 67. Similarly thesignal from the Q channel mixer 68 is passed to pre-amplifier 69 andlock-in amplifier 70. The lock-in frequency is provided bymicroprocessor 71. The gain of the lock-in amplifiers 67, 70 is softwarecontrolled to set the gain to maximise the resolution of the analog todigital converters.

Respective anti-alias filters 72 and 73 provide filtering beforedigitiser 74. Signals from a vibration sensor 75 are also directed tothe digitiser 74. The digitised signals are passed to microprocessor 71for analysis.

Steps 58 to 61 are identical to the steps performed in the priorembodiment. At step 62, as much of the vibration induced signal isremoved as possible. This can be done by passing the signal through aneural net configured as an adaptive filter. The LMS (least mean square)algorithm for determining tap weights developed by Widrow is a suitableexample. This is linear, recursive filter which requires an initialtemplate of a vibration induced signal. It passes the received signalthrough a filter tuned to remove the template-like signal, computes anRMS residual vibration-like signal and estimates new tap weights for thefilter coefficients. It performs multiple passes, with new estimates,until the LMS residual shows no further

The microprocessor 35 implements a neural net algorithm and a hiddenMarkov chain processor with optional Kalman filter as representedschematically in FIG. 2. Signals from the receiver 33 are input at 40.Other signals can also be input such as vibration sensor signals 41,ambient noise signals 42 and reference signals stored in memory 43 forcomparison.

The neural net algorithm performs pattern recognition on the signal byfinding a best fit to stored signal templates. It does so by a learningprocess, using input, output and hidden layers as analogues of neuronsand synapses.

The outputs from the algorithm include, for example, indications oftermites 44, cockroaches 45, vibrations 46 and noise 47. The number ofhidden layers required is determined empirically in a neural netdevelopment system. The training of the net depends on the depth of thedata base and variations between signals of recognised termites. Detailson neural nets can be found in “Neural Network PC Tools, A PracticalGuide”, edited by R C Eberhart and Roy W Robbins, Academic Press Inc1990, ISBN 0-12-228649-5.)

Also indicated in FIG. 13 is a Hidden Markov chain processor. Furtherdetails of the operation and implementation of hidden Markov algorithmsmay be found in “Frequency Tracking using Hidden Markov Models withAmplitude and Phase Information” by Ross F Barrett and David AHoldsworth which appeared in IEEE Transactions on Signal Processing, vol41, no. 10, October 1993, pp 2965-2976.

Hidden Markov Model tracking is achieved by obtaining overlapping FFT'sof the signal time series and assigning probabilities to causalrelationships between frequency bins in adjacent FFT's. Eventuallydeterministic signals are all that survive this process and theprobabilities of tracking such events tend to 1.

An alternative indicated in FIG. 13 is a Kalman filter. The Kalmanfilter uses position and velocity measurements to predict new values andcompare them with actual new measurements in order to obtain a betterestimation. Kalman filter techniques have been applied in various radartracking applications and may be adapted for tracking termites or groupsof termites. The Hidden Markov Model or Kalman filter trackingalgorithms may be used as alternative processes to enhance the signalquality before the pattern recognition by the neural net.

FIG. 14a and FIG. 14b show representative near field microwave antennapatterns. Insect motion is detected by small changes in the amplitudeand phase of reflected signals. It is speculated that two insect relatedmechanisms lead to detectable signals. These are:

(a) insects moving into the field of view or tracing out fluctuations inthe near field amplitude pattern or providing a changing reflectionfacet back to the radar assembly. This echo can be observed for anyinsect motion with respect to the radar.

(b) the Doppler effect due to insect motion across the near fieldequi-phase contours. This is the effect used in police radar speeddetectors.

Both of these effects are manifest in the frequency range from 0.1 Hz to10 Hz. The reflection signal strength is believed to be related to:

1. The microwave properties of the insect (ie. dielectric constant andabsorption coefficient);

2. The size/wavelength ratio of the insect;

3. The separation between the radar assembly and the insect;

4. The angle to the insect relative to the radar assembly boresight;

5. The properties of any intervening materials; and

6. The microwave polarization.

It will be appreciated from a consideration of FIG. 14a and FIG. 14bthat the near field equi-phase contours are curved with significantwiggles. It is extremely unlikely that an insect would follow such acurved and convoluted path and therefore must produce phase shifts dueto motion through the microwave field. In the case of termites therewill always be some signal since termites are always moving and willtherefore produce amplitude and phase shifts in the reflected signal.

As shown in FIG. 4 when the near field 24.125 GHZ signal is transmittedinto a non-infested part of a building, random noise or clutter isdominant at the output of amplifier 7. However as shown in FIG. 5, whenthe near field 24.125 GHZ signal is transmitted into a termite infestedpart of a building the resultant signal at the output of amplifier 7 isindicative of the presence of termites. The resultant signal is muchlarger and is displayed at a lower sensitivity as is evident by the lowlevel of fluctuations. Furthermore, the graph of FIG. 6 shows that whena Fourier transform of the signals from FIGS. 4 and 5 is undertaken, itis apparent that termites can be detected by the spectralcharacteristics at the output of amplifier 7. Finally, because signalattenuation can be strongly dependent upon wall anisotropy it isbeneficial to use a circular polarised transmitted signal.

Throughout the specification the aim has been to describe the preferredembodiments of the invention without limiting the invention to any oneembodiment or specific collection of features.

What is claimed is:
 1. A method of detecting insects in a structureincluding the steps of: transmitting a near field microwave signal intoa part of the structure; receiving a receive signal dependent on thenear field signal; and processing the receive signal to provide anoutput signal indicative of the presence of the insects in the nearfield microwave signal.
 2. The method of claim 1 wherein the step oftransmitting a near field microwave signal involves transmitting amodulated signal.
 3. The method of claim 1 wherein the step oftransmitting is further characterised by the near field microwave signalbeing less than 2 meters from a transmitter transmitting said signal. 4.The method of claim 3 wherein the transmitter is closely adjacent saidpart of the structure.
 5. The method of claim 1 wherein the step oftransmitting is further characterised by the near field signal beingnormal to said part of the structure.
 6. The method of claim 1 whereinthe near field microwave signal is circular polarized.
 7. The method ofclaim 1 wherein the receive signal is a reflected signal.
 8. The methodof claim 1 wherein the method is further characterised by the steps oftransmitting and receiving being effected by a common antenna.
 9. Themethod of claim 1 wherein the step of receiving includes the step ofmixing the signal dependent on the near field signal with a referencesignal to provide a receive signal which is a combined signal.
 10. Themethod of claim 9 wherein the combined signal comprises a beat frequencysignal component.
 11. The method of claim 2 wherein the step ofreceiving a receive signal involves receiving a signal synchronous withthe modulation frequency of the transmitted signal.
 12. The method ofclaim 1 wherein the step of processing includes the steps of filteringand amplifying the receive signal.
 13. The method of claim 12 whereinthe step of filtering is characterised by the filtering being effectedby a low pass filter having a cut-off frequency of less than 50 HZ. 14.The method of claim 12 wherein the step of filtering is characterised bythe filtering being effected by a band pass filter having an uppercut-off frequency of less than 50 HZ and a lower cut-off frequency ofgreater than 0.01 HZ.
 15. The method of claim 1 wherein the step ofprocessing further includes the steps of digitizing and analysing thereceive signal to provide said output signal indicative of the presenceof said insects in said near field microwave signal.
 16. The method ofclaim 15 wherein the step of analysing includes analysis of spectralcharacteristics of the receive signal.
 17. The method of claim 15wherein the step of analysis includes an analysis of spectralcharacteristics by Fourier transformation.
 18. The method of claim 1wherein the step of processing the receive signal includes adaptiverecognition of termite indicative signals.
 19. The method of claim 18wherein the adaptive recognition is performed in a neural network. 20.The method of claim 18 wherein the adaptive recognition is performed ina neural network and a hidden Markov chain processor algorithm and/or aKalman filter algorithm are employed at the input to the neural networkto enhance the signal to noise ratio of the signal input to the neuralnetwork.
 21. The method of claim 1 further including the step ofdisplaying the output signal.
 22. A system for detecting insects in astructure, the system comprising: signal generator means operativelycoupled to transmitter means to thereby transmit a near field microwavesignal into a part of a structure; receiver means for receiving signalsindicative of the presence or otherwise of insects in a near field ofthe microwave signal; and processor means for processing the receivedsignal to provide an output signal indicating the presence or otherwiseof insects.
 23. The system of claim 22 wherein said transmitter means isadapted to transmit a circular polarized field.
 24. The system of claim22 wherein the transmitter means comprises a transmitting antenna. 25.The system of claim 22 wherein the receiver means comprises a receivingantenna.
 26. The system of claim 22 wherein the transmitter means andthe receiver means comprise a common antenna.
 27. The system of claim 22wherein the system further comprises modulator means operatively coupledto the signal generator means for modulating the transmitted microwavesignal at a selected frequency.
 28. The system of claim 27 wherein thereceiver means comprises a synchronous rectifier for locking on receivesignals synchronous with the modulated transmitted microwave signal. 29.The system of claim 22 wherein the receiver means comprises a receivingantenna and further comprises mixing means operatively coupled to thereceiving antenna and the signal generator means, said mixing meansproviding a receive signal dependent upon an indicative signal receivedfrom said receiving antenna and a reference signal from said signalgenerator.
 30. The system of claim 22 wherein the processor meansincludes filter means for filtering said receive signal.
 31. The systemof claim 30 wherein the filter means is suitably adapted to rejectfrequencies other than frequencies indicative of the presence of insectsin the near field.
 32. The system of claim 30 wherein the filter meansis a low pass filter having a cut-off frequency of less than 50 HZ. 33.The system of claim 30 wherein the filter means is a band pass filter inwhich the upper cut-off frequency is less than 50 HZ and the lowercut-off frequency is greater than 0.01 HZ.
 34. The system of claim 22wherein the processor means includes amplification means for amplifyingthe receive signal.
 35. The system of claim 22 wherein the processormeans includes digitizing means for digitizing said receive signal. 36.The system of claim 22 wherein the processor means is a microprocessorperforming one or more of digitizing, amplifying and filtering tasks insoftware.
 37. The system of claim 36 wherein the microprocessor isprogrammed with a neural network algorithm.
 38. The system of claim 36wherein the microprocessor is programmed with a neural network algorithmand is further programmed with a hidden Markov chain processor algorithmand/or a Kalman filter algorithm to enhance the signal to noise ratio ofthe receive signal input to the neural network.
 39. The system of claim22 further comprising display means for displaying the output signal.40. A method of detecting insects in a structure including the steps of:transmitting a near field microwave signal into a part of the structure;receiving a receive signal that is amplitude modulated and/or phaseshifted in relation to the transmitted near field microwave signalsubstantially by the insects crossing near field equal amplitudecontours; and digitizing and analyzing the receive signal to provide anoutput signal indicative of the presence of the insects in the nearfield microwave signal.
 41. The method of claim 40 further comprisingadaptive recognition of termite indicative signals in a neural network.42. The method of claim 41 wherein a hidden Markov chain processoralgorithm and/or a Kalman filter algorithm are employed at an input tothe neural network to enhance the signal to noise ratio of a signalinput to the neural network.
 43. A system for detecting insects in astructure, the system comprising: signal generator means operativelycoupled to transmitter means to thereby transmit a near field microwavesignal into a part of the structure; receiver means for receivingsignals that are amplitude modulated and/or phase shifted in relation tothe transmitted near field microwave signal substantially by the insectscrossing near field equal amplitude contours and are indicative of thepresence or otherwise of insects in a near field of the microwavesignal; and processor means for digitizing and analyzing a receivesignal to provide an output signal indicating the presence or otherwiseof insects.
 44. The system of claim 43 wherein the processor means is amicroprocessor programmed with a neural network algorithm.
 45. Thesystem of claim 44 wherein the microprocessor is further programmed witha Markov chain processor algorithm and/or a Kalman filter algorithm toenhance the signal to noise ratio of the receive signal input to theneural network.